# US 9,518,808 B2 · Ammunition and weapon type identification based on spectroscopic gunshot residue analysis > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 9,518,808 B2 - Document ID: US9518808B2 - Status: Granted - Kind: B2 - Application number: 13/578,925 - Filed: 2011-02-16 - Published: 2013-02-21 - Granted: 2016-12-13 - Earliest claimed: 2010-02-16 - Assignees: The Research Foundation of State University of New York - Applicants: Igor K. Lednev; Justin Bueno - Inventors: Igor K. Lednev; Justin Bueno - Web page: https://patentgrep.com/patent/US9518808B2 ## CPC - F42B 35/00: Testing or checking of ammunition {(apparatus for measuring the energy of projectiles G01L5/14)} - G01N 21/65: Raman scattering - F42B: EXPLOSIVE CHARGES, e.g. FOR BLASTING, FIREWORKS, AMMUNITION (explosive compositions C06B; fuzes F42C; blasting F42D) - G01N: INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES (measuring or testing apparatus or processes other than immunoassay, involving enzymes or microorganisms C12M, C12Q) ## Abstract The present invention relates to a method of identifying ammunition type and/or weapon type used to fire the ammunition from gunshot residue. This method involves providing a sample including a gunshot residue, subjecting the sample to spectroscopic analysis to produce a spectroscopic signature for the sample, and identifying the spectroscopic signature to ascertain the type of ammunition and/or the type of weapon used to fire the ammunition. A method of establishing reference spectroscopic signatures for ammunition type and/or weapon type used to fire the ammunition is also disclosed. ## Claims ### Claim 1 A method of identifying ammunition type or weapon type used to fire the ammunition from gunshot residue, said method comprising: providing a statistical model for identifying ammunition type or weapon type, wherein the statistical model for identifying ammunition type or weapon type is based on principle component analysis (PCA) and support vector machines (SVM), support vector machines discriminant analysis (SVMDA), or partial least squares discriminant analysis (PLS-DA) and based on spectroscopic signatures of the known samples comprising gunshot residues from known types of ammunition or types of weapons used to fire the ammunition; providing a sample comprising gunshot residue; subjecting the sample to spectroscopic analysis to produce a spectroscopic signature for the sample, wherein the spectroscopic analysis is selected from the group consisting of Raman spectroscopy and infrared spectroscopy and the spectroscopic signature is obtained from the spectra at: different locations on a single particle of gunshot residue; different particles of gunshot residue from a single discharge; particles of gunshot residue from different discharges of the same firearm; or particles of gunshot residue from different discharges of different firearms; and applying the spectroscopic signature for the sample to the statistical model to ascertain the type of ammunition or the type of weapon used to fire the ammunition. ### Claim 2 (depends on 1) The method of claim 1, wherein the statistical model is for identifying the type of ammunition. ### Claim 3 (depends on 1) The method of claim 1, wherein the statistical model is for identifying the type of weapon used to fire the ammunition. ### Claim 4 (depends on 1) The method of claim 1, wherein the statistical model is for identifying the type of ammunition which is selected from the group consisting of 9 mm caliber, .45 caliber, .40 caliber, .22 L caliber, and .38 Special. ### Claim 5 (depends on 1) The method of claim 1, wherein the spectroscopic analysis is Raman spectroscopy. ### Claim 6 A method of establishing a statistical model for determination of ammunition type or weapon type used to fire the ammunition, said method comprising: providing known samples comprising gunshot residues from known types of ammunition or types of weapons used to fire the ammunition; subjecting each known sample to spectroscopic analysis to produce a spectroscopic signature for each known sample, wherein the spectroscopic analysis is selected from the group consisting of Raman spectroscopy and infrared spectroscopy and the spectroscopic signature is obtained from the spectra at: different locations on a single particle of gunshot residue; different particles of gunshot residue from a single discharge; particles of gunshot residue from different discharges of the same firearm; or particles of gunshot residue from different discharges of different firearms; and establishing a statistical model based on principle component analysis (PCA) and support vector machines (SVM), support vector machines discriminant analysis (SVMDA), or partial least squares discriminant analysis (PLS-DA) for determination of the type of ammunition or the type of weapon used to fire ammunition based on the spectroscopic signature obtained for each known sample subjected to spectroscopic analysis. ### Claim 7 (depends on 6) The method of claim 6, wherein the spectroscopic analysis is Raman spectroscopy. ### Claim 8 (depends on 1) The method of claim 1, wherein the spectroscopic analysis is infrared spectroscopy. ### Claim 9 (depends on 8) The method of claim 8, wherein the infrared spectroscopy is Fourier transform infrared spectroscopy. ### Claim 10 (depends on 6) The method of claim 6, wherein the spectroscopic analysis is infrared spectroscopy. ### Claim 11 (depends on 10) The method of claim 10, wherein the infrared spectroscopy is Fourier transform infrared spectroscopy. ### Claim 12 (depends on 5) The method of claim 5, wherein the Raman spectroscopy is selected from the group consisting of conventional Raman spectroscopy, Raman microspectroscopy, surface enhanced Raman spectroscopy (SERS), tip enhanced Raman spectroscopy (TERS), and coherent anti-Stokes Raman spectroscopy (CARS). ### Claim 13 (depends on 7) The method of claim 7, wherein the Raman spectroscopy is selected from the group consisting of conventional Raman spectroscopy, Raman microspectroscopy, surface enhanced Raman spectroscopy (SERS), tip enhanced Raman spectroscopy (TERS), and coherent anti-Stokes Raman spectroscopy (CARS). ### Claim 14 (depends on 6) The method of claim 6, wherein the statistical model is for determination of ammunition type. ### Claim 15 (depends on 6) The method of claim 6, wherein the statistical model is for determination of weapon type.